In this page
1. Main results
- 459 teachers working in schools in Wales are on the shielded patient list (SPL). This represents 1.6% of teachers in Wales.
- The percentage of teachers that are on the SPL varies by local authority, with the highest percentage in Merthyr Tydfil (2.5%) and the lowest percentage in the Isle of Anglesey (0.8%).
- 574 teaching assistants working in schools in Wales are on the SPL. This represents 2.3% of teaching assistants in Wales.
- Denbighshire has the highest percentage of teaching assistants on the SPL (3.3%) while Gwynedd has the lowest percentage (1.3%).
2. Staff on the Shielded Patient List by school phase and medium
There are 416 teachers on the SPL split evenly across primary schools and middle and secondary schools. Twenty-one teachers on the SPL work in special schools and pupil referral units (PRUs) whilst the remainder do not have a school recorded.
There are 112 teachers working in Welsh medium schools that are on the SPL compared with 304 teachers working in English medium schools. The remainder work in schools that do not follow the national curriculum (Special schools and PRUs) or do not have a school recorded.
Primary schools in Wales have 385 teaching assistants on the SPL whilst middle and secondary schools have 109. There are 62 teaching assistants on the SPL that work in special schools and pupil referral units (PRUs) while the remainder do not have a school recorded.
There are 117 teaching assistants on the Shielded Patient List that work in Welsh medium schools compared with 377 that work in English medium schools. The remainder work in schools that do not follow the national curriculum (Special schools and PRUs) or do not have a school recorded.
3. Dataset information
The shielded patient list is a list of clinically extremely vulnerable people. They are deemed most likely to become unwell if they catch coronavirus. Shielded people should have received a letter or been told by their GP that they are in this group. The Shielded Patient List is derived using a variety of data sources drawn from the Health Service. More information on the sources and methodology can be accessed on the NHS Wales Informatics Service.
The School Workforce Annual Census (SWAC) is comprised of two data collections relating to the 2018/2019 academic year. The first is data on contracts and pay from local authorities and the second is data on the workforce directly from schools. The two data collections contain overlapping but not identical staff records. Therefore, some staff members may appear on one data collection but not the other. We used both data collections for our analysis.
4. Quality and methodology information
The Administrative Data Research Unit (ADRU) in Welsh Government undertakes research projects for the public good using established administrative datasets. During the coronavirus (COVID-19) pandemic, ADRU has undertaken a number of data linking projects. One of these projects involved linking the SPL and SWAC to estimate the number of teachers and teaching assistants shielding in Wales. This analysis uses the SPL as of 15 June 2020 when there were 127,095 unique NHS numbers on the list, and the SWAC collection as at 05 November 2019. Four schools out of 1,502 did not return information for the SWAC collection so their data are missing from this analysis. See the SWAC website for further information on SWAC data.
To obtain a complete picture of the school workforce, we used SWAC data from local authorities and schools. We combined workforce identifying information from local authorities returns and school returns, starting with the local authorities staff list in full, and adding in staff from the school returns that did not appear on the local authorities returns. This gave us a complete workforce list. Only staff without a recorded contract end date or with a contract end date after the start of lockdown on 23 March were included in the analysis.
We linked this workforce list to the shielded patient list using first name, last name and date of birth as the linking fields. As with every data linking exercise where there is no unique field common to the datasets being linked there is a risk of false matches. However, using a combination of three fields in this analysis should minimise this risk. There is also a risk that the linking process does not pick up genuine matches between the shielded patient list and school workforce if, for example there are errors in the different data sources or inconsistencies, e.g. if marital surname is used in medical records but not in school workforce records. Although it is not possible to quantify this risk it is likely to be a small one.
Local authorities have different administrative systems to record their school workforce data, so how individuals’ contracts are recorded may differ. It is possible some individuals working as teachers or teaching assistants were recorded with contract categories different from the contract categories we are using to identify teaching and teaching assistant staff in this analysis, so may have been missed. The figures for teaching assistants should be treated with particular caution as there are a many different codes that can be used for categorising support staff and the use of these may vary by local authority and school. For example, special needs support staff may be recorded as teaching assistants.
Staff can have more than one contract of the same or different kinds with the same or different local authorities. Our figures count individual roles for a given medium, phase and local authority. If a staff member has more than one role, or works across phases, mediums or local authorities they could be counted more than once.
Teachers includes all qualified classroom teachers, leadership teachers (headteachers, deputy heads, assistant heads etc), permanent supply teachers working in schools long term, unqualified teachers and trainee teachers. Teaching assistants includes teaching assistants, higher level teaching assistants and foreign language teaching assistants.
Welsh medium schools include schools recorded as Welsh medium, bilingual, transitional and dual stream. English medium schools include schools recorded as English medium and English with significant Welsh. Special schools, pupil referral unit and nursery schools do not follow the national curriculum so are not included in splits by Welsh medium.
The data manipulation was done in Spyder using Python 3.7, on the Welsh Government UKSeRP (UK Secure Research Platform).
This research has been carried out as part of the ADR Wales programme of work. The ADR Wales programme of work is aligned to the priority themes as identified in the Welsh Government’s national strategy: Prosperity for All. ADR Wales brings together data science experts at Swansea University Medical School, staff from the Wales Institute of Social and Economic Research, Data and Methods (WISERD) at Cardiff University and specialist teams within the Welsh Government to develop new evidence which supports Prosperity for All by using the SAIL Databank at Swansea University, to link and analyse anonymised data. ADR Wales is part of the Economic and Social Research Council (part of UK Research and Innovation) funded ADR UK (grant ES/S007393/1).